Search Results for author: Danda Pani Paudel

Found 66 papers, 29 papers with code

Towards a Generalist and Blind RGB-X Tracker

1 code implementation28 May 2024 Yuedong Tan, Zongwei Wu, Yuqian Fu, Zhuyun Zhou, Guolei Sun, Chao Ma, Danda Pani Paudel, Luc van Gool, Radu Timofte

With the emergence of a single large model capable of successfully solving a multitude of tasks in NLP, there has been growing research interest in achieving similar goals in computer vision.

Inductive Bias Multi-Label Classification +1

CaLDiff: Camera Localization in NeRF via Pose Diffusion

no code implementations23 Dec 2023 Rashik Shrestha, Bishad Koju, Abhigyan Bhusal, Danda Pani Paudel, François Rameau

This paper studies the problem of localizing cameras in NeRF using a diffusion model for camera pose adjustment.

Camera Localization

Ternary-type Opacity and Hybrid Odometry for RGB-only NeRF-SLAM

no code implementations20 Dec 2023 Junru Lin, Asen Nachkov, Songyou Peng, Luc van Gool, Danda Pani Paudel

To foster this line of research, we also propose a simple yet novel visual odometry scheme that uses a hybrid combination of volumetric and warping-based image renderings.

Visual Odometry

Lego: Learning to Disentangle and Invert Concepts Beyond Object Appearance in Text-to-Image Diffusion Models

no code implementations23 Nov 2023 Saman Motamed, Danda Pani Paudel, Luc van Gool

To enable customized content creation based on a few example images of a concept, methods such as Textual Inversion and DreamBooth invert the desired concept and enable synthesizing it in new scenes.

Language Modelling Large Language Model +3

Model-aware 3D Eye Gaze from Weak and Few-shot Supervisions

1 code implementation20 Nov 2023 Nikola Popovic, Dimitrios Christodoulou, Danda Pani Paudel, Xi Wang, Luc van Gool

In this work, we propose to predict 3D eye gaze from weak supervision of eye semantic segmentation masks and direct supervision of a few 3D gaze vectors.

Semantic Segmentation

Deformable Neural Radiance Fields using RGB and Event Cameras

no code implementations ICCV 2023 Qi Ma, Danda Pani Paudel, Ajad Chhatkuli, Luc van Gool

In this work, we develop a novel method to model the deformable neural radiance fields using RGB and event cameras.

Prior Based Online Lane Graph Extraction from Single Onboard Camera Image

no code implementations25 Jul 2023 Yigit Baran Can, Alexander Liniger, Danda Pani Paudel, Luc van Gool

Thus, online estimation of the lane graph is crucial for widespread and reliable autonomous navigation.

Autonomous Navigation

Improving Online Lane Graph Extraction by Object-Lane Clustering

no code implementations ICCV 2023 Yigit Baran Can, Alexander Liniger, Danda Pani Paudel, Luc van Gool

In this work, we propose an architecture and loss formulation to improve the accuracy of local lane graph estimates by using 3D object detection outputs.

3D Object Detection Autonomous Driving +4

Online Lane Graph Extraction from Onboard Video

no code implementations3 Apr 2023 Yigit Baran Can, Alexander Liniger, Danda Pani Paudel, Luc van Gool

One of the most common and useful representation of such an understanding is done in the form of BEV lane graphs.

Autonomous Driving Navigate

NeRF-GAN Distillation for Efficient 3D-Aware Generation with Convolutions

1 code implementation22 Mar 2023 Mohamad Shahbazi, Evangelos Ntavelis, Alessio Tonioni, Edo Collins, Danda Pani Paudel, Martin Danelljan, Luc van Gool

Pose-conditioned convolutional generative models struggle with high-quality 3D-consistent image generation from single-view datasets, due to their lack of sufficient 3D priors.

Image Generation Inductive Bias

Surface Normal Clustering for Implicit Representation of Manhattan Scenes

1 code implementation ICCV 2023 Nikola Popovic, Danda Pani Paudel, Luc van Gool

In this work, we aim to leverage the geometric prior of Manhattan scenes to improve the implicit neural radiance field representations.

Clustering Novel View Synthesis

Robust RGB-D Fusion for Saliency Detection

1 code implementation2 Aug 2022 Zongwei Wu, Shriarulmozhivarman Gobichettipalayam, Brahim Tamadazte, Guillaume Allibert, Danda Pani Paudel, Cédric Demonceaux

In this work, we aim for RGB-D saliency detection that is robust to the low-quality depths which primarily appear in two forms: inaccuracy due to noise and the misalignment to RGB.

Saliency Detection

Gradient Obfuscation Checklist Test Gives a False Sense of Security

no code implementations3 Jun 2022 Nikola Popovic, Danda Pani Paudel, Thomas Probst, Luc van Gool

It has since become a trend to use these five characteristics as a sufficient test, to determine whether or not gradient obfuscation is the main source of robustness.

Spatially Multi-conditional Image Generation

no code implementations25 Mar 2022 Ritika Chakraborty, Nikola Popovic, Danda Pani Paudel, Thomas Probst, Luc van Gool

However, multi-conditional image generation is a very challenging problem due to the heterogeneity and the sparsity of the (in practice) available conditioning labels.

Conditional Image Generation Missing Labels

Transforming Model Prediction for Tracking

1 code implementation CVPR 2022 Christoph Mayer, Martin Danelljan, Goutam Bhat, Matthieu Paul, Danda Pani Paudel, Fisher Yu, Luc van Gool

Optimization based tracking methods have been widely successful by integrating a target model prediction module, providing effective global reasoning by minimizing an objective function.

Ranked #21 on Visual Object Tracking on LaSOT (Precision metric)

Inductive Bias Visual Object Tracking

Unsupervised Domain Adaptation for Nighttime Aerial Tracking

2 code implementations CVPR 2022 Junjie Ye, Changhong Fu, Guangze Zheng, Danda Pani Paudel, Guang Chen

Previous advances in object tracking mostly reported on favorable illumination circumstances while neglecting performance at nighttime, which significantly impeded the development of related aerial robot applications.

Object Discovery Object Tracking +1

Collapse by Conditioning: Training Class-conditional GANs with Limited Data

1 code implementation ICLR 2022 Mohamad Shahbazi, Martin Danelljan, Danda Pani Paudel, Luc van Gool

On the contrary, we observe that class-conditioning causes mode collapse in limited data settings, where unconditional learning leads to satisfactory generative ability.

Generative Adversarial Network

Improving the Behaviour of Vision Transformers with Token-consistent Stochastic Layers

no code implementations30 Dec 2021 Nikola Popovic, Danda Pani Paudel, Thomas Probst, Luc van Gool

We use linear layers with token-consistent stochastic parameters inside the multilayer perceptron blocks, without altering the architecture of the transformer.

Adversarial Robustness Transfer Learning

Topology Preserving Local Road Network Estimation from Single Onboard Camera Image

1 code implementation CVPR 2022 Yigit Baran Can, Alexander Liniger, Danda Pani Paudel, Luc van Gool

We represent the road topology using a set of directed lane curves and their interactions, which are captured using their intersection points.

End-to-End Learning of Multi-category 3D Pose and Shape Estimation

no code implementations19 Dec 2021 Yigit Baran Can, Alexander Liniger, Danda Pani Paudel, Luc van Gool

We use a Transformer-based architecture to detect the keypoints, as well as to summarize the visual context of the image.

Structured Bird's-Eye-View Traffic Scene Understanding from Onboard Images

2 code implementations ICCV 2021 Yigit Baran Can, Alexander Liniger, Danda Pani Paudel, Luc van Gool

In this work, we study the problem of extracting a directed graph representing the local road network in BEV coordinates, from a single onboard camera image.

Autonomous Navigation Lane Detection +1

TACS: Taxonomy Adaptive Cross-Domain Semantic Segmentation

1 code implementation10 Sep 2021 Rui Gong, Martin Danelljan, Dengxin Dai, Danda Pani Paudel, Ajad Chhatkuli, Fisher Yu, Luc van Gool

In many real-world settings, the target domain task requires a different taxonomy than the one imposed by the source domain.

Contrastive Learning Domain Adaptation +1

GANmut: Learning Interpretable Conditional Space for Gamut of Emotions

no code implementations CVPR 2021 Stefano d'Apolito, Danda Pani Paudel, Zhiwu Huang, Andres Romero, Luc van Gool

On the other hand, learning from inexpensive and intuitive basic categorical emotion labels leads to limited emotion variability.

Learning to Relate Depth and Semantics for Unsupervised Domain Adaptation

1 code implementation CVPR 2021 Suman Saha, Anton Obukhov, Danda Pani Paudel, Menelaos Kanakis, Yuhua Chen, Stamatios Georgoulis, Luc van Gool

Specifically, we show that: (1) our approach improves performance on all tasks when they are complementary and mutually dependent; (2) the CTRL helps to improve both semantic segmentation and depth estimation tasks performance in the challenging UDA setting; (3) the proposed ISL training scheme further improves the semantic segmentation performance.

Monocular Depth Estimation Multi-Task Learning +4

Learning Target Candidate Association to Keep Track of What Not to Track

1 code implementation ICCV 2021 Christoph Mayer, Martin Danelljan, Danda Pani Paudel, Luc van Gool

To tackle the problem of lacking ground-truth correspondences between distractor objects in visual tracking, we propose a training strategy that combines partial annotations with self-supervision.

Visual Object Tracking Visual Tracking

Unsupervised Robust Domain Adaptation without Source Data

no code implementations26 Mar 2021 Peshal Agarwal, Danda Pani Paudel, Jan-Nico Zaech, Luc van Gool

This paper aims at answering the question of finding the right strategy to make the target model robust and accurate in the setting of unsupervised domain adaptation without source data.

Image Classification Unsupervised Domain Adaptation

Unsupervised Monocular Depth Reconstruction of Non-Rigid Scenes

no code implementations31 Dec 2020 Ayça Takmaz, Danda Pani Paudel, Thomas Probst, Ajad Chhatkuli, Martin R. Oswald, Luc van Gool

In this work, we present an unsupervised monocular framework for dense depth estimation of dynamic scenes, which jointly reconstructs rigid and non-rigid parts without explicitly modelling the camera motion.

Depth Estimation Motion Segmentation

An Efficient Recurrent Adversarial Framework for Unsupervised Real-Time Video Enhancement

no code implementations24 Dec 2020 Dario Fuoli, Zhiwu Huang, Danda Pani Paudel, Luc van Gool, Radu Timofte

Video enhancement is a challenging problem, more than that of stills, mainly due to high computational cost, larger data volumes and the difficulty of achieving consistency in the spatio-temporal domain.

Video Enhancement

CompositeTasking: Understanding Images by Spatial Composition of Tasks

1 code implementation CVPR 2021 Nikola Popovic, Danda Pani Paudel, Thomas Probst, Guolei Sun, Luc van Gool

Learning to perform spatially distributed tasks is motivated by the frequent availability of only sparse labels across tasks, and the desire for a compact multi-tasking network.

Decoder

Cluster, Split, Fuse, and Update: Meta-Learning for Open Compound Domain Adaptive Semantic Segmentation

no code implementations CVPR 2021 Rui Gong, Yuhua Chen, Danda Pani Paudel, Yawei Li, Ajad Chhatkuli, Wen Li, Dengxin Dai, Luc van Gool

Open compound domain adaptation (OCDA) is a domain adaptation setting, where target domain is modeled as a compound of multiple unknown homogeneous domains, which brings the advantage of improved generalization to unseen domains.

Domain Adaptation Meta-Learning +2

Soft Contrastive Learning for Visual Localization

1 code implementation NeurIPS 2020 Janine Thoma, Danda Pani Paudel, Luc V. Gool

Our soft assignment makes a gradual distinction between close and far images in both geometric and feature spaces.

Contrastive Learning Image Retrieval +2

Facial Emotion Recognition with Noisy Multi-task Annotations

1 code implementation19 Oct 2020 Siwei Zhang, Zhiwu Huang, Danda Pani Paudel, Luc van Gool

In our formulation, we exploit a new method to enable the emotion prediction and the joint distribution learning in a unified adversarial learning game.

Facial Emotion Recognition

Learning Condition Invariant Features for Retrieval-Based Localization from 1M Images

1 code implementation27 Aug 2020 Janine Thoma, Danda Pani Paudel, Ajad Chhatkuli, Luc van Gool

Image features for retrieval-based localization must be invariant to dynamic objects (e. g. cars) as well as seasonal and daytime changes.

Retrieval

Self-Calibration Supported Robust Projective Structure-from-Motion

no code implementations4 Jul 2020 Rui Gong, Danda Pani Paudel, Ajad Chhatkuli, Luc van Gool

In this paper, we propose a unified SfM method, in which the matching process is supported by self-calibration constraints.

Camera Calibration valid

Geometrically Mappable Image Features

1 code implementation21 Mar 2020 Janine Thoma, Danda Pani Paudel, Ajad Chhatkuli, Luc van Gool

This is achieved by guiding the learning process such that the feature and geometric distances between images are directly proportional.

Image Retrieval Retrieval

Unsupervised Learning of Category-Specific Symmetric 3D Keypoints from Point Sets

1 code implementation ECCV 2020 Clara Fernandez-Labrador, Ajad Chhatkuli, Danda Pani Paudel, Jose J. Guerrero, Cédric Demonceaux, Luc van Gool

This paper aims at learning category-specific 3D keypoints, in an unsupervised manner, using a collection of misaligned 3D point clouds of objects from an unknown category.

Domain Agnostic Feature Learning for Image and Video Based Face Anti-spoofing

no code implementations15 Dec 2019 Suman Saha, Wen-Hao Xu, Menelaos Kanakis, Stamatios Georgoulis, Yu-Hua Chen, Danda Pani Paudel, Luc van Gool

Face anti-spoofing is a measure towards this direction for bio-metric user authentication, and in particular face recognition, that tries to prevent spoof attacks.

Face Anti-Spoofing Face Recognition

Convex Relaxations for Consensus and Non-Minimal Problems in 3D Vision

no code implementations ICCV 2019 Thomas Probst, Danda Pani Paudel, Ajad Chhatkuli, Luc van Gool

Notably, we further exploit the POP formulation of non-minimal solver also for the generic consensus maximization problems in 3D vision.

Sliced Wasserstein Generative Models

1 code implementation CVPR 2019 Jiqing Wu, Zhiwu Huang, Dinesh Acharya, Wen Li, Janine Thoma, Danda Pani Paudel, Luc van Gool

In generative modeling, the Wasserstein distance (WD) has emerged as a useful metric to measure the discrepancy between generated and real data distributions.

Image Generation Video Generation

Towards High Resolution Video Generation with Progressive Growing of Sliced Wasserstein GANs

1 code implementation4 Oct 2018 Dinesh Acharya, Zhiwu Huang, Danda Pani Paudel, Luc van Gool

Furthermore, we introduce a sliced version of Wasserstein GAN (SWGAN) loss to improve the distribution learning on the video data of high-dimension and mixed-spatiotemporal distribution.

Action Recognition Image Generation +2

Sampling Algebraic Varieties for Robust Camera Autocalibration

no code implementations ECCV 2018 Danda Pani Paudel, Luc van Gool

This paper addresses the problem of robustly autocalibrating a moving camera with constant intrinsics.

Incremental Non-Rigid Structure-from-Motion with Unknown Focal Length

no code implementations ECCV 2018 Thomas Probst, Danda Pani Paudel, Ajad Chhatkuli, Luc van Gool

In this paper we present a method for incremental Non-Rigid Structure-from-Motion (NRSfM) with the perspective camera model and the isometric surface prior with unknown focal length.

Model-free Consensus Maximization for Non-Rigid Shapes

no code implementations ECCV 2018 Thomas Probst, Ajad Chhatkuli, Danda Pani Paudel, Luc van Gool

In this paper, we formulate the model-free consensus maximization as an Integer Program in a graph using `rules' on measurements.

Face Translation between Images and Videos using Identity-aware CycleGAN

no code implementations4 Dec 2017 Zhiwu Huang, Bernhard Kratzwald, Danda Pani Paudel, Jiqing Wu, Luc van Gool

This paper presents a new problem of unpaired face translation between images and videos, which can be applied to facial video prediction and enhancement.

Image-to-Image Translation Translation +1

Improving Video Generation for Multi-functional Applications

1 code implementation30 Nov 2017 Bernhard Kratzwald, Zhiwu Huang, Danda Pani Paudel, Acharya Dinesh, Luc van Gool

In this paper, we aim to improve the state-of-the-art video generative adversarial networks (GANs) with a view towards multi-functional applications.

Colorization Future prediction +2

Optimal Transformation Estimation With Semantic Cues

no code implementations ICCV 2017 Danda Pani Paudel, Adlane Habed, Luc van Gool

This paper addresses the problem of estimating the geometric transformation relating two distinct visual modalities (e. g. an image and a map, or a projective structure and a Euclidean 3D model) while relying only on semantic cues, such as semantically segmented regions or object bounding boxes.

Consensus Maximization With Linear Matrix Inequality Constraints

no code implementations CVPR 2017 Pablo Speciale, Danda Pani Paudel, Martin R. Oswald, Till Kroeger, Luc van Gool, Marc Pollefeys

While randomized methods like RANSAC are fast, they do not guarantee global optimality and fail to manage large amounts of outliers.

Sliced Wasserstein Generative Models

1 code implementation8 Jun 2017 Jiqing Wu, Zhiwu Huang, Dinesh Acharya, Wen Li, Janine Thoma, Danda Pani Paudel, Luc van Gool

In generative modeling, the Wasserstein distance (WD) has emerged as a useful metric to measure the discrepancy between generated and real data distributions.

Image Generation Video Generation

Robust and Optimal Sum-of-Squares-Based Point-to-Plane Registration of Image Sets and Structured Scenes

no code implementations ICCV 2015 Danda Pani Paudel, Adlane Habed, Cedric Demonceaux, Pascal Vasseur

This paper deals with the problem of registering a known structured 3D scene and its metric Structure-from-Motion (SfM) counterpart.

LMI-Based 2D-3D Registration: From Uncalibrated Images to Euclidean Scene

no code implementations CVPR 2015 Danda Pani Paudel, Adlane Habed, Cedric Demonceaux, Pascal Vasseur

This paper investigates the problem of registering a scanned scene, represented by 3D Euclidean point coordinates, and two or more uncalibrated cameras.

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